Overview

Dataset statistics

Number of variables15
Number of observations5408
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory633.9 KiB
Average record size in memory120.0 B

Variable types

Numeric15

Alerts

df_index is highly correlated with passing_accuracy and 1 other fieldsHigh correlation
np_goals_p90 is highly correlated with goal_conversion_np and 1 other fieldsHigh correlation
shooting_accuracy is highly correlated with goal_conversion_npHigh correlation
goal_conversion_np is highly correlated with np_goals_p90 and 2 other fieldsHigh correlation
passing_accuracy is highly correlated with df_indexHigh correlation
assists_p90 is highly correlated with scoring_contributionHigh correlation
scoring_contribution is highly correlated with np_goals_p90 and 2 other fieldsHigh correlation
tackles_p90 is highly correlated with df_indexHigh correlation
df_index is highly correlated with passing_accuracyHigh correlation
np_goals_p90 is highly correlated with goal_conversion_np and 1 other fieldsHigh correlation
shooting_accuracy is highly correlated with goal_conversion_npHigh correlation
goal_conversion_np is highly correlated with np_goals_p90 and 2 other fieldsHigh correlation
passing_accuracy is highly correlated with df_indexHigh correlation
assists_p90 is highly correlated with scoring_contributionHigh correlation
scoring_contribution is highly correlated with np_goals_p90 and 2 other fieldsHigh correlation
np_goals_p90 is highly correlated with goal_conversion_np and 1 other fieldsHigh correlation
goal_conversion_np is highly correlated with np_goals_p90 and 1 other fieldsHigh correlation
scoring_contribution is highly correlated with np_goals_p90 and 1 other fieldsHigh correlation
df_index is highly correlated with passing_accuracyHigh correlation
np_goals_p90 is highly correlated with shots_p90 and 2 other fieldsHigh correlation
shots_p90 is highly correlated with np_goals_p90 and 1 other fieldsHigh correlation
shooting_accuracy is highly correlated with goal_conversion_npHigh correlation
goal_conversion_np is highly correlated with np_goals_p90 and 2 other fieldsHigh correlation
passing_accuracy is highly correlated with df_indexHigh correlation
assists_p90 is highly correlated with key_passes_p90 and 1 other fieldsHigh correlation
key_passes_p90 is highly correlated with assists_p90High correlation
scoring_contribution is highly correlated with np_goals_p90 and 3 other fieldsHigh correlation
df_index has unique values Unique
np_goals_p90 has 788 (14.6%) zeros Zeros
shooting_accuracy has 71 (1.3%) zeros Zeros
goal_conversion_np has 788 (14.6%) zeros Zeros
assists_p90 has 1723 (31.9%) zeros Zeros
dribbles_success_ratio has 169 (3.1%) zeros Zeros
scoring_contribution has 450 (8.3%) zeros Zeros
tackles_p90 has 1181 (21.8%) zeros Zeros
interceptions_p90 has 546 (10.1%) zeros Zeros
avg_team_position has 330 (6.1%) zeros Zeros

Reproduction

Analysis started2021-12-08 15:46:49.952209
Analysis finished2021-12-08 15:47:30.886728
Duration40.93 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

df_index
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct5408
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14493.02829
Minimum11
Maximum28980
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:30.970537image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile1462.6
Q17331.25
median14594.5
Q321681.75
95-th percentile27474.5
Maximum28980
Range28969
Interquartile range (IQR)14350.5

Descriptive statistics

Standard deviation8384.811806
Coefficient of variation (CV)0.57854105
Kurtosis-1.200155493
Mean14493.02829
Median Absolute Deviation (MAD)7184
Skewness-0.006764192535
Sum78378297
Variance70305069.02
MonotonicityStrictly increasing
2021-12-08T16:47:31.109166image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
232431
 
< 0.1%
226721
 
< 0.1%
259221
 
< 0.1%
115831
 
< 0.1%
282931
 
< 0.1%
238691
 
< 0.1%
54361
 
< 0.1%
177221
 
< 0.1%
74811
 
< 0.1%
54321
 
< 0.1%
Other values (5398)5398
99.8%
ValueCountFrequency (%)
111
< 0.1%
121
< 0.1%
301
< 0.1%
311
< 0.1%
321
< 0.1%
361
< 0.1%
491
< 0.1%
501
< 0.1%
661
< 0.1%
671
< 0.1%
ValueCountFrequency (%)
289801
< 0.1%
289791
< 0.1%
289771
< 0.1%
289711
< 0.1%
289651
< 0.1%
289621
< 0.1%
289461
< 0.1%
289441
< 0.1%
289431
< 0.1%
289401
< 0.1%

np_goals_p90
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct3206
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2758666657
Minimum0
Maximum1.590106007
Zeros788
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:31.294640image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1337295691
median0.2516700387
Q30.3933351641
95-th percentile0.649546133
Maximum1.590106007
Range1.590106007
Interquartile range (IQR)0.259605595

Descriptive statistics

Standard deviation0.2053185059
Coefficient of variation (CV)0.7442671823
Kurtosis1.463787821
Mean0.2758666657
Median Absolute Deviation (MAD)0.1278417741
Skewness0.9140052691
Sum1491.886928
Variance0.04215568888
MonotonicityNot monotonic
2021-12-08T16:47:31.557935image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0788
 
14.6%
0.35433070878
 
0.1%
0.2980132458
 
0.1%
0.24793388438
 
0.1%
0.20454545457
 
0.1%
0.28391167197
 
0.1%
0.30201342287
 
0.1%
0.2513966487
 
0.1%
0.22613065337
 
0.1%
0.23746701857
 
0.1%
Other values (3196)4554
84.2%
ValueCountFrequency (%)
0788
14.6%
0.023461939521
 
< 0.1%
0.034013605441
 
< 0.1%
0.034142640361
 
< 0.1%
0.039318479691
 
< 0.1%
0.041379310341
 
< 0.1%
0.041724617521
 
< 0.1%
0.042492917851
 
< 0.1%
0.042816365371
 
< 0.1%
0.043816942551
 
< 0.1%
ValueCountFrequency (%)
1.5901060071
< 0.1%
1.2739383851
< 0.1%
1.2561060711
< 0.1%
1.2356979411
< 0.1%
1.229718191
< 0.1%
1.2058465291
< 0.1%
1.1842105261
< 0.1%
1.1688311691
< 0.1%
1.1356466881
< 0.1%
1.1310592461
< 0.1%

shots_p90
Real number (ℝ≥0)

HIGH CORRELATION

Distinct4454
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.26902098
Minimum0
Maximum6.989528796
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:31.743440image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9953921606
Q11.667129801
median2.186575353
Q32.79327548
95-th percentile3.800205973
Maximum6.989528796
Range6.989528796
Interquartile range (IQR)1.126145679

Descriptive statistics

Standard deviation0.8676639754
Coefficient of variation (CV)0.3823957483
Kurtosis0.8884223626
Mean2.26902098
Median Absolute Deviation (MAD)0.5594702772
Skewness0.6243413246
Sum12270.86546
Variance0.7528407742
MonotonicityNot monotonic
2021-12-08T16:47:31.985791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211
 
0.2%
2.43243243210
 
0.2%
1.6981132088
 
0.1%
1.6666666678
 
0.1%
2.48
 
0.1%
1.6363636367
 
0.1%
2.022471917
 
0.1%
2.6470588247
 
0.1%
1.9148936177
 
0.1%
2.0930232567
 
0.1%
Other values (4444)5328
98.5%
ValueCountFrequency (%)
06
0.1%
0.21
 
< 0.1%
0.20156774921
 
< 0.1%
0.22613065331
 
< 0.1%
0.23936170211
 
< 0.1%
0.25568181821
 
< 0.1%
0.25787965621
 
< 0.1%
0.29605263161
 
< 0.1%
0.30791788861
 
< 0.1%
0.30963302751
 
< 0.1%
ValueCountFrequency (%)
6.9895287961
 
< 0.1%
6.3978127141
 
< 0.1%
6.0919540231
 
< 0.1%
5.9241353661
 
< 0.1%
5.9178905211
 
< 0.1%
5.8991596641
 
< 0.1%
5.8695652173
0.1%
5.8333333331
 
< 0.1%
5.8064516131
 
< 0.1%
5.7311320751
 
< 0.1%

shooting_accuracy
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct829
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4150445686
Minimum0
Maximum1
Zeros71
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:32.176282image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2
Q10.3333333333
median0.4126984127
Q30.5
95-th percentile0.6428571429
Maximum1
Range1
Interquartile range (IQR)0.1666666667

Descriptive statistics

Standard deviation0.1391235485
Coefficient of variation (CV)0.3352014676
Kurtosis1.345089194
Mean0.4150445686
Median Absolute Deviation (MAD)0.08597156811
Skewness0.1054956914
Sum2244.561027
Variance0.01935536175
MonotonicityNot monotonic
2021-12-08T16:47:32.336854image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5338
 
6.2%
0.3333333333234
 
4.3%
0.4146
 
2.7%
0.375104
 
1.9%
0.4285714286103
 
1.9%
0.25102
 
1.9%
0.285714285784
 
1.6%
0.666666666779
 
1.5%
0.444444444475
 
1.4%
071
 
1.3%
Other values (819)4072
75.3%
ValueCountFrequency (%)
071
1.3%
0.058823529413
 
0.1%
0.066666666671
 
< 0.1%
0.076923076924
 
0.1%
0.083333333335
 
0.1%
0.090909090916
 
0.1%
0.111
 
0.2%
0.111111111115
 
0.3%
0.11538461541
 
< 0.1%
0.11764705881
 
< 0.1%
ValueCountFrequency (%)
118
0.3%
0.88888888891
 
< 0.1%
0.85714285712
 
< 0.1%
0.83333333336
 
0.1%
0.82352941182
 
< 0.1%
0.81818181821
 
< 0.1%
0.812
0.2%
0.78571428573
 
0.1%
0.77777777785
 
0.1%
0.77272727271
 
< 0.1%

goal_conversion_np
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct638
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1220080723
Minimum0
Maximum0.6666666667
Zeros788
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:32.492438image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.06378143133
median0.1153846154
Q30.1692307692
95-th percentile0.2727272727
Maximum0.6666666667
Range0.6666666667
Interquartile range (IQR)0.1054493379

Descriptive statistics

Standard deviation0.08685916013
Coefficient of variation (CV)0.7119132243
Kurtosis1.792484474
Mean0.1220080723
Median Absolute Deviation (MAD)0.05286214953
Skewness0.8688464478
Sum659.8196549
Variance0.007544513698
MonotonicityNot monotonic
2021-12-08T16:47:32.674982image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0788
 
14.6%
0.1666666667155
 
2.9%
0.125153
 
2.8%
0.1111111111136
 
2.5%
0.2135
 
2.5%
0.1428571429132
 
2.4%
0.1124
 
2.3%
0.08333333333107
 
2.0%
0.25100
 
1.8%
0.09090909091100
 
1.8%
Other values (628)3478
64.3%
ValueCountFrequency (%)
0788
14.6%
0.016129032262
 
< 0.1%
0.018518518521
 
< 0.1%
0.018867924531
 
< 0.1%
0.019607843141
 
< 0.1%
0.021
 
< 0.1%
0.020408163273
 
0.1%
0.021276595742
 
< 0.1%
0.021739130431
 
< 0.1%
0.022222222221
 
< 0.1%
ValueCountFrequency (%)
0.66666666672
 
< 0.1%
0.6251
 
< 0.1%
0.57142857141
 
< 0.1%
0.53333333331
 
< 0.1%
0.512
0.2%
0.46666666671
 
< 0.1%
0.46153846151
 
< 0.1%
0.45454545451
 
< 0.1%
0.44444444441
 
< 0.1%
0.43753
 
0.1%

passing_accuracy
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5342
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5149557717
Minimum0
Maximum0.9076331361
Zeros5
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:32.851476image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02091753877
Q10.09119391026
median0.6651405362
Q30.7351512605
95-th percentile0.8057748401
Maximum0.9076331361
Range0.9076331361
Interquartile range (IQR)0.6439573502

Descriptive statistics

Standard deviation0.3020706313
Coefficient of variation (CV)0.5865952921
Kurtosis-1.083853631
Mean0.5149557717
Median Absolute Deviation (MAD)0.09067855825
Skewness-0.840052697
Sum2784.880813
Variance0.09124666628
MonotonicityNot monotonic
2021-12-08T16:47:32.993098image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
05
 
0.1%
0.734
 
0.1%
0.013
 
0.1%
0.753
 
0.1%
0.023
 
0.1%
0.7253
 
0.1%
0.623
 
0.1%
0.034444444442
 
< 0.1%
0.6742
 
< 0.1%
0.6676543212
 
< 0.1%
Other values (5332)5378
99.4%
ValueCountFrequency (%)
05
0.1%
0.013
0.1%
0.010694444441
 
< 0.1%
0.011032258061
 
< 0.1%
0.011646586351
 
< 0.1%
0.011651376151
 
< 0.1%
0.011917808221
 
< 0.1%
0.0121
 
< 0.1%
0.012049180331
 
< 0.1%
0.012079207921
 
< 0.1%
ValueCountFrequency (%)
0.90763313611
< 0.1%
0.89386363641
< 0.1%
0.88726415091
< 0.1%
0.86881422921
< 0.1%
0.86788533831
< 0.1%
0.86622641511
< 0.1%
0.86565880721
< 0.1%
0.86564304461
< 0.1%
0.86552028221
< 0.1%
0.86425911561
< 0.1%

assists_p90
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct2571
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1213521475
Minimum0
Maximum1.162790698
Zeros1723
Zeros (%)31.9%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:33.136714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.09795919093
Q30.1903251787
95-th percentile0.3533918872
Maximum1.162790698
Range1.162790698
Interquartile range (IQR)0.1903251787

Descriptive statistics

Standard deviation0.1260277362
Coefficient of variation (CV)1.038529097
Kurtosis3.392562946
Mean0.1213521475
Median Absolute Deviation (MAD)0.09795919093
Skewness1.420375889
Sum656.2724136
Variance0.01588299028
MonotonicityNot monotonic
2021-12-08T16:47:33.281327image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01723
31.9%
0.19230769237
 
0.1%
0.27692307697
 
0.1%
0.14754098367
 
0.1%
0.26011560696
 
0.1%
0.26470588246
 
0.1%
0.12080536916
 
0.1%
0.16014234886
 
0.1%
0.15652173916
 
0.1%
0.26865671646
 
0.1%
Other values (2561)3628
67.1%
ValueCountFrequency (%)
01723
31.9%
0.022607385081
 
< 0.1%
0.023376623381
 
< 0.1%
0.023461939521
 
< 0.1%
0.026262036771
 
< 0.1%
0.026369762671
 
< 0.1%
0.027051397661
 
< 0.1%
0.027649769591
 
< 0.1%
0.028391167191
 
< 0.1%
0.028499050031
 
< 0.1%
ValueCountFrequency (%)
1.1627906981
< 0.1%
0.96774193551
< 0.1%
0.88524590161
< 0.1%
0.83487940631
< 0.1%
0.79295154191
< 0.1%
0.77809798271
< 0.1%
0.77170418011
< 0.1%
0.77142857141
< 0.1%
0.76013513511
< 0.1%
0.74175824181
< 0.1%

key_passes_p90
Real number (ℝ≥0)

HIGH CORRELATION

Distinct4185
Distinct (%)77.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.151965157
Minimum0
Maximum5.934065934
Zeros40
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:33.429930image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3911464659
Q10.7679416387
median1.058823529
Q31.431818182
95-th percentile2.23476298
Maximum5.934065934
Range5.934065934
Interquartile range (IQR)0.6638765431

Descriptive statistics

Standard deviation0.5828555368
Coefficient of variation (CV)0.5059662899
Kurtosis3.2698623
Mean1.151965157
Median Absolute Deviation (MAD)0.3284242272
Skewness1.243450172
Sum6229.827571
Variance0.3397205767
MonotonicityNot monotonic
2021-12-08T16:47:33.557589image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
040
 
0.7%
1.7647058829
 
0.2%
1.29
 
0.2%
1.1258
 
0.1%
1.4516129037
 
0.1%
1.3043478267
 
0.1%
0.95744680857
 
0.1%
0.94736842117
 
0.1%
1.3636363647
 
0.1%
1.1538461547
 
0.1%
Other values (4175)5300
98.0%
ValueCountFrequency (%)
040
0.7%
0.065549890751
 
< 0.1%
0.080142475511
 
< 0.1%
0.088669950741
 
< 0.1%
0.10895883781
 
< 0.1%
0.11479591841
 
< 0.1%
0.13533834591
 
< 0.1%
0.14173228351
 
< 0.1%
0.14705882351
 
< 0.1%
0.15490533561
 
< 0.1%
ValueCountFrequency (%)
5.9340659341
< 0.1%
4.9586776861
< 0.1%
4.6956521741
< 0.1%
4.5534687621
< 0.1%
4.1602465331
< 0.1%
4.1373966941
< 0.1%
4.0206185571
< 0.1%
3.9534883721
< 0.1%
3.9009287931
< 0.1%
3.8297872341
< 0.1%

dribbles_p90
Real number (ℝ≥0)

Distinct4649
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.116164187
Minimum0
Maximum10.67114094
Zeros44
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:33.814901image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4087890827
Q11.069114471
median1.78807947
Q32.868785727
95-th percentile4.880578101
Maximum10.67114094
Range10.67114094
Interquartile range (IQR)1.799671256

Descriptive statistics

Standard deviation1.428824018
Coefficient of variation (CV)0.675195255
Kurtosis1.94960152
Mean2.116164187
Median Absolute Deviation (MAD)0.848298205
Skewness1.228292358
Sum11444.21593
Variance2.041538075
MonotonicityNot monotonic
2021-12-08T16:47:33.950538image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
044
 
0.8%
2.6470588248
 
0.1%
1.9565217397
 
0.1%
2.4324324326
 
0.1%
2.1951219516
 
0.1%
2.3684210536
 
0.1%
1.1842105266
 
0.1%
1.8755
 
0.1%
1.9354838715
 
0.1%
0.85714285715
 
0.1%
Other values (4639)5310
98.2%
ValueCountFrequency (%)
044
0.8%
0.048205677561
 
< 0.1%
0.091836734691
 
< 0.1%
0.095880681821
 
< 0.1%
0.099667774091
 
< 0.1%
0.10380622841
 
< 0.1%
0.10514018691
 
< 0.1%
0.1068883611
 
< 0.1%
0.10948905111
 
< 0.1%
0.10955569081
 
< 0.1%
ValueCountFrequency (%)
10.671140941
< 0.1%
9.4153846151
< 0.1%
9.1968325791
< 0.1%
9.0618860511
< 0.1%
8.8732394371
< 0.1%
8.8568588471
< 0.1%
8.7699680511
< 0.1%
8.523676881
< 0.1%
8.4957789721
< 0.1%
8.3227040821
< 0.1%

dribbles_success_ratio
Real number (ℝ≥0)

ZEROS

Distinct903
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5007151952
Minimum0
Maximum1
Zeros169
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:34.091361image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.191875
Q10.4101019462
median0.5
Q30.6052631579
95-th percentile0.7692307692
Maximum1
Range1
Interquartile range (IQR)0.1951612116

Descriptive statistics

Standard deviation0.1771917557
Coefficient of variation (CV)0.3538773286
Kurtosis1.271757877
Mean0.5007151952
Median Absolute Deviation (MAD)0.1
Skewness-0.3223419537
Sum2707.867776
Variance0.03139691827
MonotonicityNot monotonic
2021-12-08T16:47:34.237380image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5469
 
8.7%
0.3333333333174
 
3.2%
0.6666666667173
 
3.2%
0169
 
3.1%
0.6124
 
2.3%
0.4112
 
2.1%
0.4285714286111
 
2.1%
192
 
1.7%
0.571428571491
 
1.7%
0.62582
 
1.5%
Other values (893)3811
70.5%
ValueCountFrequency (%)
0169
3.1%
0.058823529411
 
< 0.1%
0.071428571431
 
< 0.1%
0.076923076921
 
< 0.1%
0.081
 
< 0.1%
0.083333333332
 
< 0.1%
0.090909090914
 
0.1%
0.15
 
0.1%
0.11111111113
 
0.1%
0.12510
 
0.2%
ValueCountFrequency (%)
192
1.7%
0.91666666672
 
< 0.1%
0.90909090912
 
< 0.1%
0.93
 
0.1%
0.89473684211
 
< 0.1%
0.88888888891
 
< 0.1%
0.8755
 
0.1%
0.857142857115
 
0.3%
0.851
 
< 0.1%
0.84615384624
 
0.1%

scoring_contribution
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct3636
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3972188131
Minimum0
Maximum1.777378815
Zeros450
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:34.392553image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2269622855
median0.3711340206
Q30.5357142857
95-th percentile0.8546618492
Maximum1.777378815
Range1.777378815
Interquartile range (IQR)0.3087520002

Descriptive statistics

Standard deviation0.2510291796
Coefficient of variation (CV)0.6319669949
Kurtosis1.369287861
Mean0.3972188131
Median Absolute Deviation (MAD)0.1532163451
Skewness0.8136578663
Sum2148.159341
Variance0.06301564903
MonotonicityNot monotonic
2021-12-08T16:47:34.525423image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0450
 
8.3%
0.32608695658
 
0.1%
0.33707865178
 
0.1%
0.2513966488
 
0.1%
0.26470588247
 
0.1%
0.52785923757
 
0.1%
0.37815126057
 
0.1%
0.247
 
0.1%
0.25423728817
 
0.1%
0.20454545457
 
0.1%
Other values (3626)4892
90.5%
ValueCountFrequency (%)
0450
8.3%
0.04540867811
 
< 0.1%
0.046923879041
 
< 0.1%
0.053571428571
 
< 0.1%
0.054811205851
 
< 0.1%
0.055900621121
 
< 0.1%
0.056390977441
 
< 0.1%
0.057397959181
 
< 0.1%
0.058823529411
 
< 0.1%
0.059249506251
 
< 0.1%
ValueCountFrequency (%)
1.7773788151
< 0.1%
1.6957431961
< 0.1%
1.6666666671
< 0.1%
1.6475972541
< 0.1%
1.5901060071
< 0.1%
1.5027829311
< 0.1%
1.4987190441
< 0.1%
1.4944649451
< 0.1%
1.4616321561
< 0.1%
1.4516129031
< 0.1%

tackles_p90
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct4226
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6110768801
Minimum0
Maximum5.189211527
Zeros1181
Zeros (%)21.8%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:34.669364image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1014866729
median0.4952806996
Q30.9166652769
95-th percentile1.755945635
Maximum5.189211527
Range5.189211527
Interquartile range (IQR)0.815178604

Descriptive statistics

Standard deviation0.5943806971
Coefficient of variation (CV)0.9726774427
Kurtosis2.824765419
Mean0.6110768801
Median Absolute Deviation (MAD)0.4088627725
Skewness1.366195804
Sum3304.703768
Variance0.353288413
MonotonicityNot monotonic
2021-12-08T16:47:34.833715image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01181
 
21.8%
0.14854426622
 
< 0.1%
0.37055335972
 
< 0.1%
0.62205722831
 
< 0.1%
0.98630078931
 
< 0.1%
0.64960706191
 
< 0.1%
0.12892155161
 
< 0.1%
1.0434538471
 
< 0.1%
0.27248357211
 
< 0.1%
1.3655645511
 
< 0.1%
Other values (4216)4216
78.0%
ValueCountFrequency (%)
01181
21.8%
0.02838615261
 
< 0.1%
0.028906932521
 
< 0.1%
0.032157787541
 
< 0.1%
0.032764206921
 
< 0.1%
0.033071699441
 
< 0.1%
0.033852912861
 
< 0.1%
0.034409457251
 
< 0.1%
0.035657403671
 
< 0.1%
0.035852574211
 
< 0.1%
ValueCountFrequency (%)
5.1892115271
< 0.1%
4.2840848091
< 0.1%
4.2253527041
< 0.1%
4.0510856271
< 0.1%
3.7110402091
< 0.1%
3.6921744531
< 0.1%
3.4653302361
< 0.1%
3.4103522141
< 0.1%
3.3204726251
< 0.1%
3.2519276041
< 0.1%

interceptions_p90
Real number (ℝ≥0)

ZEROS

Distinct4844
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3918477149
Minimum0
Maximum3.605033531
Zeros546
Zeros (%)10.1%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:34.990299image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1588938535
median0.3090475635
Q30.544161111
95-th percentile1.052846014
Maximum3.605033531
Range3.605033531
Interquartile range (IQR)0.3852672575

Descriptive statistics

Standard deviation0.3425027805
Coefficient of variation (CV)0.8740711441
Kurtosis5.296550511
Mean0.3918477149
Median Absolute Deviation (MAD)0.1800984715
Skewness1.744946988
Sum2119.112442
Variance0.1173081547
MonotonicityNot monotonic
2021-12-08T16:47:35.153429image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0546
 
10.1%
0.099650117372
 
< 0.1%
0.070924221412
 
< 0.1%
0.18752
 
< 0.1%
0.18936206032
 
< 0.1%
0.28030397412
 
< 0.1%
0.34690101762
 
< 0.1%
0.33865141482
 
< 0.1%
0.45351473922
 
< 0.1%
0.19660098742
 
< 0.1%
Other values (4834)4844
89.6%
ValueCountFrequency (%)
0546
10.1%
0.022100749951
 
< 0.1%
0.024993057481
 
< 0.1%
0.025174825171
 
< 0.1%
0.027258189571
 
< 0.1%
0.02748343361
 
< 0.1%
0.027796308651
 
< 0.1%
0.03039575271
 
< 0.1%
0.030786702881
 
< 0.1%
0.031745583841
 
< 0.1%
ValueCountFrequency (%)
3.6050335311
< 0.1%
3.0349493861
< 0.1%
2.5439815781
< 0.1%
2.4772791721
< 0.1%
2.3017050331
< 0.1%
2.2276099591
< 0.1%
2.1775238161
< 0.1%
2.1559937461
< 0.1%
2.1027263571
< 0.1%
2.0627929231
< 0.1%

avg_team_position
Real number (ℝ≥0)

ZEROS

Distinct221
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4146597062
Minimum0
Maximum1
Zeros330
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:35.326778image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2105263158
median0.3703703704
Q30.5769230769
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0.3663967611

Descriptive statistics

Standard deviation0.2705362379
Coefficient of variation (CV)0.6524295318
Kurtosis-0.43057487
Mean0.4146597062
Median Absolute Deviation (MAD)0.1798941799
Skewness0.5675051129
Sum2242.479691
Variance0.07318985604
MonotonicityNot monotonic
2021-12-08T16:47:35.484356image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0330
 
6.1%
1303
 
5.6%
0.2857142857182
 
3.4%
0.5174
 
3.2%
0.3333333333166
 
3.1%
0.4285714286129
 
2.4%
0.6666666667102
 
1.9%
0.142857142997
 
1.8%
0.190476190575
 
1.4%
0.357142857163
 
1.2%
Other values (211)3787
70.0%
ValueCountFrequency (%)
0330
6.1%
0.037037037047
 
0.1%
0.0384615384610
 
0.2%
0.041666666678
 
0.1%
0.043478260877
 
0.1%
0.045454545458
 
0.1%
0.0476190476222
 
0.4%
0.055
 
0.1%
0.052631578954
 
0.1%
0.055555555566
 
0.1%
ValueCountFrequency (%)
1303
5.6%
0.9629629635
 
0.1%
0.96153846155
 
0.1%
0.968
 
0.1%
0.95833333332
 
< 0.1%
0.952380952424
 
0.4%
0.954
 
0.1%
0.94444444443
 
0.1%
0.94117647066
 
0.1%
0.93759
 
0.2%

avg_league_cov
Real number (ℝ≥0)

Distinct68
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4174555504
Minimum0.2154786051
Maximum0.7650138775
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2021-12-08T16:47:35.638615image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.2154786051
5-th percentile0.3098386677
Q10.360566052
median0.4154162093
Q30.4676203588
95-th percentile0.5228169653
Maximum0.7650138775
Range0.5495352724
Interquartile range (IQR)0.1070543069

Descriptive statistics

Standard deviation0.08300991535
Coefficient of variation (CV)0.1988473151
Kurtosis4.218489885
Mean0.4174555504
Median Absolute Deviation (MAD)0.05390112087
Skewness0.9591620338
Sum2257.599617
Variance0.006890646047
MonotonicityNot monotonic
2021-12-08T16:47:35.962272image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.360566052123
 
2.3%
0.4070386632122
 
2.3%
0.3311984356120
 
2.2%
0.4641257259102
 
1.9%
0.7650138775101
 
1.9%
0.476890283899
 
1.8%
0.309838667798
 
1.8%
0.434805499897
 
1.8%
0.379045729496
 
1.8%
0.479278209796
 
1.8%
Other values (58)4354
80.5%
ValueCountFrequency (%)
0.215478605189
1.6%
0.229850359662
1.1%
0.296834050766
1.2%
0.309838667798
1.8%
0.311242529279
1.5%
0.316112993964
1.2%
0.316846255877
1.4%
0.324009645662
1.1%
0.3311984356120
2.2%
0.331464539463
1.2%
ValueCountFrequency (%)
0.7650138775101
1.9%
0.533233453993
1.7%
0.52415014275
1.4%
0.522816965395
1.8%
0.513111211183
1.5%
0.503756027877
1.4%
0.503000643178
1.4%
0.502821984768
1.3%
0.493837018576
1.4%
0.487470200886
1.6%

Interactions

2021-12-08T16:47:28.140052image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:53.344618image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:55.614184image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:57.850699image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:00.137561image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:02.384708image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:04.984030image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:07.449392image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:09.817435image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:12.267845image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:14.778202image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:17.193887image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:19.736784image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:22.381155image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:25.821994image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:28.277684image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:53.480255image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:55.804682image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:57.988331image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:00.279211image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:02.538126image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:05.130604image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:07.596970image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:09.963818image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:12.414453image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:14.959354image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:17.368466image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:19.880405image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:22.619519image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:25.979574image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:28.432271image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:53.629776image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:55.963685image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:58.133941image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:00.439785image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:02.696039image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:05.291206image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:07.758566image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:10.119371image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:12.581008image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:15.115991image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:17.650718image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:20.032021image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:22.893785image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:26.139112image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:47:28.573892image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:53.780878image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-12-08T16:46:56.110810image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
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Correlations

2021-12-08T16:47:36.115432image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-12-08T16:47:36.421584image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-12-08T16:47:36.748710image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-12-08T16:47:37.067857image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-12-08T16:47:30.365123image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
A simple visualization of nullity by column.
2021-12-08T16:47:30.732142image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

df_indexnp_goals_p90shots_p90shooting_accuracygoal_conversion_nppassing_accuracyassists_p90key_passes_p90dribbles_p90dribbles_success_ratioscoring_contributiontackles_p90interceptions_p90avg_team_positionavg_league_cov
0110.582.590.590.220.660.291.150.380.500.860.000.760.960.49
1120.352.940.470.120.740.171.042.940.530.520.000.680.390.35
2300.472.580.470.180.780.231.671.590.480.700.000.500.760.49
3310.513.270.460.160.760.071.271.420.490.580.000.230.500.48
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Last rows

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